Upload 4 files

Dehazing.py

@@ -42,4 +42,4 @@ if __name__ == '__main__':
     image = opt.test_path
     print(image)
     restored2,time_num = inference_img(image,Net)
-    torchvision.utils.save_image(restored2,opt.save_path+os.path.split(image)[-1])
+    torchvision.utils.save_image(restored2,opt.save_path+'output.png')

Lowlight.py

@@ -34,7 +34,7 @@ try:
     onnx_output = onnx_session.run(['output'], onnx_input)
     torch_output = np.squeeze(onnx_output[0], 0)
     torch_output = np.transpose(torch_output * 255, [1, 2, 0]).astype(np.uint8)
-    plt.imsave(config.save_path+os.path.split(config.test_path)[-1], torch_output)
+    plt.imsave(config.save_path+'output.png', torch_output)
 except Exception as e:
     print(f'Input on model:{model_name} failed')
     print(e)

SuperResolution.py

@@ -44,4 +44,4 @@ if __name__ == '__main__':
     image=opt.test_path
     print(image)
     restored2,time_num=inference_img(image,Net,device)
-    torchvision.utils.save_image(restored2,opt.save_path+os.path.split(image)[-1])
+    torchvision.utils.save_image(restored2,opt.save_path+'output.png')

Underwater.py

@@ -44,4 +44,4 @@ if __name__ == '__main__':
     image = opt.test_path
     print(image)
     restored2,time_num = inference_img(image,Net,device)
-    torchvision.utils.save_image(restored2,opt.save_path+os.path.split(image)[-1])
+    torchvision.utils.save_image(restored2,opt.save_path+'output.png')